Update app.py

app.py

@@ -4,16 +4,27 @@ import traceback
 
 def detect_emotion(img):
     try:
+        # DeepFace handles preprocessing and detection; enforce_detection=False avoids crashes on non-perfect faces
         result = DeepFace.analyze(img, actions=['emotion'], enforce_detection=False)
-        emotion = result['dominant_emotion']
-        return f"Emotion: {emotion}"
+        emotion = result.get('dominant_emotion', None)
+        scores = result.get('emotion', {})
+        lines = []
+        if emotion:
+            lines.append(f"Dominant emotion: {emotion}")
+        if scores:
+            for k, v in sorted(scores.items(), key=lambda x: -x[1]):
+                lines.append(f"{k}: {v:.2f}")
+        return "\\n".join(lines) if lines else "No result"
     except Exception as e:
-        return "Error: " + str(e) + "\n" + traceback.format_exc()
+        return "Error during analysis:\\n" + str(e) + "\\n" + traceback.format_exc()
 
-gr.Interface(
+iface = gr.Interface(
     fn=detect_emotion,
-    inputs=gr.Image(type="numpy"),
-    outputs="text",
+    inputs=gr.Image(type="numpy", label="Upload face image"),
+    outputs=gr.Textbox(label="Emotion Output"),
     title="Emotion Detection (DeepFace)",
-    description="Upload an image to detect emotion using pretrained DeepFace model."
-).launch()
+    description="Detect facial emotions using DeepFace pretrained models."
+)
+
+if __name__ == "__main__":
+    iface.launch()